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| 2 | date = 2024-01-26 | |
| 3 | title = "Building an Audit Status Dashboard" | |
| 4 | description = "Learn how to utilize Alteryx Designer and Power BI Desktop to build a simple status tracking dashboard for an audit or other engagement." | |
| 5 | +++ | |
| 6 | ||
| 7 | Alteryx and Power BI are powerful tools that can help turn your old-school audit trackers into interactive tools that provide useful insights and potential action plans. | |
| 8 | ||
| 9 | With these tools, we are going to build the following dashboard: | |
| 10 | ||
| 11 |  | |
| 12 |  | |
| 13 | ||
| 14 | ## Requirements | |
| 15 | ||
| 16 | This project assumes the following: | |
| 17 | ||
| 18 | - You have access to Alteryx Designer and Power BI Desktop. | |
| 19 | - If you only have Power BI Desktop, you may need to perform some analysis in Power BI instead of Alteryx. | |
| 20 | - Your data is in a format that can be imported into Alteryx and/or Power BI. | |
| 21 | - You have a basic understanding of data types and visualization. | |
| 22 | ||
| 23 | ## Alteryx: Data Preparation & Analysis | |
| 24 | ||
| 25 | ### Import Data | |
| 26 | ||
| 27 | With Alteryx, importing data is easy with the use of the `Input Data` tool. Simply drag this tool onto the canvas from the `In/Out` tab in the Ribbon to create it as a node. | |
| 28 | ||
| 29 | You can choose the File Format manually or simply connect to your file/database and let Alteryx determine the format for you. For this example, we will be importing an Excel file and changing the `Start Data Import on Line` variable to `2`. | |
| 30 | ||
| 31 |  | |
| 32 | ||
| 33 | ### Transform Data | |
| 34 | ||
| 35 | Next, let's replace null data and remove whitespace to clean up our data. We can do this with the `Data Cleansing` tool in the `Preparation` tab in the Ribbon. | |
| 36 | ||
| 37 | Ensure that the following options are enabled: | |
| 38 | ||
| 39 | - Replace Nulls | |
| 40 | - Replace with Blanks (String Fields) | |
| 41 | - Replace with 0 (Numeric Fields) | |
| 42 | - Remove Unwanted Characters | |
| 43 | - Leading and Trailing Whitespace | |
| 44 | ||
| 45 |  | |
| 46 | ||
| 47 | For our next step, we will transform the date fields from strings to datetime format. Add a `Datetime` tool for each field you want to transform - in the example below, I am using the tool twice for the "Started On" and "Submitted On" fields. | |
| 48 | ||
| 49 |  | |
| 50 | ||
| 51 | Now that the dates are in the correct format, let's perform a calculation based on those fields. Start by adding a `Filter` tool, naming a new Output Column, and pasting the formula below into it (the two fields used in this formula must match the output of the `Datetime` tools above): | |
| 52 | ||
| 53 | ```txt | |
| 54 | DateTimeDiff([SubmittedOn_Out],[StartedOn_Out], "days") | |
| 55 | ``` | |
| 56 | ||
| 57 |  | |
| 58 | ||
| 59 | ### Export Data | |
| 60 | ||
| 61 | Finalize the process by exporting the transformed data set to a new file, for use in the following visualization step. | |
| 62 | ||
| 63 |  | |
| 64 | ||
| 65 | ## Power BI: Data Visualization | |
| 66 | ||
| 67 | ### Import Data | |
| 68 | ||
| 69 | To start, open the Power BI Desktop application. Upon first use, Power BI will ask if you want to open an existing dashboard or import new data. | |
| 70 | ||
| 71 | As we are creating our first dashboard, let's import our data. In my example below, I'm importing data from the "Tracker" sheet of the Excel file I'm using for this project. | |
| 72 | ||
| 73 | During this process, I also imported the export from the Alteryx workflow above. Therefore, we have two different files available for use in our dashboard. | |
| 74 | ||
| 75 |  | |
| 76 | ||
| 77 |  | |
| 78 | ||
| 79 | ### Add Visuals | |
| 80 | ||
| 81 | To create the dashboard below, you will need to follow the list instructions below and format as needed: | |
| 82 | ||
| 83 |  | |
| 84 |  | |
| 85 | ||
| 86 | Instructions to create the visuals above: | |
| 87 | ||
| 88 | - `Text Box`: Explain the name and purpose of the dashboard. You can also add images and logos at the top of the dashboard. | |
| 89 | - `Donut Chart`: Overall status of the project. | |
| 90 | - `Legend`: Status | |
| 91 | - `Values`: Count of Status | |
| 92 | - `Stacked Column Chart`: Task count by assignee. | |
| 93 | - `X-axis`: Preparer | |
| 94 | - `Y-axis`: Count of Control ID | |
| 95 | - `Legend`: Status | |
| 96 | - `Treemap`: Top N client submitters by average days to submit. | |
| 97 | - `Details`: Preparer | |
| 98 | - `Values`: Sum of Avg_DaysToSubmit | |
| 99 | - `Line Chart`: Projected vs. actual hours over time. | |
| 100 | - `Clustered Bar Chart`: Projected vs. actual hours per person. | |
| 101 | - `Slicer & Table` - Upcoming due dates. | |
| 102 | - `Slicer`: | |
| 103 | - `Values`: Date Due | |
| 104 | - `Table`: | |
| 105 | - `Columns`: Count of Control ID, Date Due, Preparer, Status | |
| 106 | ||
| 107 | ### Format the Dashboard | |
| 108 | ||
| 109 | You can choose a theme in the View tab of the Ribbon. You can even browse for custom JSON files that define themes, such as ones found online or custom ones created by your organization. | |
| 110 | ||
| 111 | For each visual, you can click the `Format` button in the `Visualizations` side pane and explore the options. You can custom options such as: | |
| 112 | ||
| 113 | - Visual | |
| 114 | - Legend | |
| 115 | - Colors | |
| 116 | - Data labels | |
| 117 | - Category labels | |
| 118 | - General | |
| 119 | - Properties | |
| 120 | - Title | |
| 121 | - Effects | |
| 122 | - Header icons | |
| 123 | - Tooltips | |
| 124 | - Alt text | |
| 125 | ||
| 126 | You can always look online for inspiration when trying to decide how best to organize and style your dashboard. | |
| 127 | ||
| 128 | ## Sharing the Results | |
| 129 | ||
| 130 | Generally, you have a few different options for sharing your dashboards with others: | |
| 131 | ||
| 132 | 1. Export the dashboard as a PDF in the file menu of Power BI. This will export all tabs and visuals as they are set when the export button is pressed. You will lose all interactivity with this option. | |
| 133 | 2. Send the full Power BI file to those you wish to share the dashboard. This will retain all settings and interactivity. However, you will also need to send the source files if they need to refresh the dashboard and you will need to re-send the files if you make updates. | |
| 134 | 3. Store the dashboard in a synced location, such as a shared drive or Microsoft Teams. Depending on how a user configures their local Windows paths, the data source paths may not be compatible for all users with such a setup. | |